Logan, Brent R.

Introduction: Axi-cel utilization expanded after demonstration of superior event-free survival in patients (pts) with early relapsed or primary refractory LBCL (Locke, et al. NEJM. 2022) and was reinforced by improved overall survival (OS) among these pts (Westin, et al. NEJM. 2023). Despite increased demand, limited data exist on the impact of bridging therapies (BT) on pt outcomes. Thus, BT use between leukapheresis and lymphodepletion (LD) is largely at the discretion of treating physicians. Here, we assessed the impact of BT on effectiveness and safety outcomes after axi-cel. Methods: Pts receiving axi-cel for 3L+ LBCL in the US between 2017-2020 were prospectively collected through the CIBMTR registry in a post-authorization safety study; data up to May 2023 were included. Effectiveness outcomes were overall response rate (ORR), complete response (CR) rate, duration of response (DOR), progression-free survival (PFS), and OS. Safety outcomes were cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) per ASTCT grading, non-relapse mortality (NRM), and other key adverse events. Propensity score-based inverse probability of treatment weighting (IPTW) was used in logistic and Cox regressions to account for potential confounding in BT use. For pts who had BT, effects of BT types and responses on outcomes were evaluated using conventional logistic and Cox regressions. Results: Of 1497 pts registered, 1307 had BT data available and were included (median follow-up, 36 mo). Overall, 430 pts (33%) received BT (median time from leukapheresis to LD, 23 days [IQR, 21-28]). Systemic therapy was used in 403 pts (31%), including 305 (23%) with chemotherapy (CT)-based BT (19% treated with CT + anti-CD20 monoclonal antibody [mAb; mainly rituximab] and 4% with CT only), and 98 (7%) with non-CT systemic therapy (Table). Radiotherapy (± systemic therapy) was used in 44 pts (3%). Pts with ≥3 lines of prior therapy (odds ratio [OR], 10.67 [95% CI, 7.17−15.87]) or mild hepatic impairment prior to infusion (OR, 1.64 [1.06−2.55]) were more likely to receive BT, while those with histologic transformation (OR, 0.69 [0.51−0.92]) or longer time from diagnosis to leukapheresis were less likely to receive BT. ORRs to axi-cel were 70% and 79% (CR rates 51% and 64%) for pts with or without BT, respectively. Unadjusted DOR, PFS, and OS at 3 years were 40%, 28%, and 37%, respectively, in pts with BT vs 49%, 39%, and 49%, respectively, in those without BT. After multivariate adjustment, no statistical significance was found between BT and any effectiveness outcome. Adjusted hazard ratios (HRs) for BT were 1.13 (95% CI, 0.94-1.36) for PFS and 1.11 (95% CI, 0.92-1.34) for OS, respectively (Figure). Most safety endpoints were consistent regardless of BT. Grade ≥3 CRS and ICANS occurred in 12% and 30% of pts, respectively, who received BT vs 10% and 24% of pts who did not. Use of BT was associated with more frequent prolonged neutropenia (OR, 2.24 [1.44-3.50]) and thrombocytopenia (OR, 2.33 [1.67-3.24]), but not associated with a higher rate of infections or NRM (Table). Among pts receiving BT, 74 (17%) had a CR or partial response to BT. Of them, median PFS and median OS post infusion were 12.7 mo (3.8-not estimable [NE]) and 48.7 mo (18.6-NE), respectively. Response to BT was associated with increased CR rate (OR, 2.00 [1.07-3.75]), PFS (HR, 0.69 [0.49-0.99]), and OS (HR, 0.59 [0.40-0.88]) and decreased any-grade ICANS (OR, 0.51 [0.29-0.92]). When different BT strategies were considered, effectiveness and most safety outcomes for CT + anti-CD20 mAb vs non-CT treatment were comparable without significant difference. CT + anti-CD20 mAb was associated with improved ORR (OR, 1.90 [1.00-3.60]), PFS (HR, 0.69 [0.49-0.98]), and OS (HR, 0.66 [0.46-0.95]) but increased any-grade CRS (OR, 2.16 [1.02-4.57]) vs CT only. CT use was associated with an increased risk of prolonged thrombocytopenia (41% vs 24% for pts receiving non-CT treatment; OR, 2.37 [1.39-4.02]). No significant association was found between use of radiotherapy as BT and any outcome. Conclusion: These US real-world findings suggest that the addition of BT prior to axi-cel is associated with more frequent prolonged cytopenias but does not impact effectiveness or other critical safety outcomes. Response to BT may prognosticate more favorable outcomes after axi-cel infusion. Further study is warranted to identify the optimal bridging regimen.

Background: BMT CTN 1703 was a Phase 3 trial comparing Tac/MTX (n = 217) to post-transplant cyclophosphamide (PT-Cy)/Tac/MMF (n = 214) GVHD prophylaxis after reduced intensity conditioning unrelated donor hematopoietic cell transplant (HCT). PT-Cy significantly improved GVHD-free Relapse-Free Survival (Bolanos-Meade et al NEJM 2023). However overall survival was not significantly different and the # of Grade 2 infections was higher with PT-Cy. To investigate its biologic underpinnings 1703 was linked to a mechanistic study, BMT CTN 1801, which co-enrolled 324 pts (159 CNI/MTX 165 PT-Cy). The resulting dataset enabled an analysis of post-HCT T cell reconstitution at an unprecedented level of detail. Methods: Samples were collected from the HCT infusion and on D+7, 14, 28, 63, 98, 180, 270, 1- and 2-yr. We extracted DNA (2,225 samples) and performed Adaptive Biotech β-strand T Cell Receptor (TCR) Immunosequencing (TCR-Seq). We profiled 44,077 (median) TCRs/sample resulting in 215,155,719 T cells analyzed. We evaluated multiple TCR diversity measures longitudinally and before/after cGVHD and infections. Each measure evaluates a specific aspect of TCR diversity, including Simpsons Clonality (focuses on the most expanded clones) Diversity Slope (mid-range clones) Richness (both mid-range and less-expanded clones) and Singletons (the TCR-Seq equivalent of naïve T cells). This analysis was robust to the full range (1000-50,000) of down-sampled TCRs sequenced. Results: We identified major differences in TCR reconstitution in Tac/MTX vs PT-Cy that begin early and persist through 2 yr post-HCT. These resulted in a significantly less diverse TCR repertoire with PT-Cy with substantial implications for its efficacy and toxicity. The most salient differences are: (1) PT-Cy caused significant in-vivo T cell depletion early post-HCT (% T cells/total WBC at D+28: 8.2% (Tac/MTX) vs 2.2% (PT-Cy) p=2.2x10 -23). (2) The remaining donor T cells in PT-Cy undergo substantial clonal expansion ( Fig 1) resulting in significantly constrained TCR diversity measured by Clonality, Slope, Richness, Singletons (not shown) and Singletons/Richness ( Fig 2) which began early (D+14) and persisted for 2 yr. (3) Linked T cell depletion and clonal expansion resulted in a TCR diversity bottleneck after PT-Cy ( Fig 1). Due to the bottleneck, while the fraction of T cells originating from the transplant infusion at =/> 1 yr was similar between arms (18% vs 24%, p=0.7) there were significantly fewer Singleton TCRs in PT-Cy, suggesting a reduction in naïve T cells ( Fig 2), an outcome that has critical consequences for both cGVHD and infection. Thus while cGVHD onset with Tac/MTX was linked to a significant drop in TCR diversity due to singleton clonal expansion (median log-2 fold change in singletons with Tac/MTX = -0.25 p = 0.01) this drop was not observed with PT-Cy (log-2 fold change = -0.05, p = 0.1). Along with the significantly decreased # singletons at all time-points in PT-Cy ( Fig 2) this suggests that while cGVHD after Tac/MTX is linked to substantial naïve T cell expansion, the same is not true with PT-Cy, identifying a novel mechanism for cGVHD control with PT-Cy. The substantially fewer singletons in PT-Cy vs Tac/MTX may also increase the risk of Grade 2+ infections. T cell responses to new infections rely on antigen recognition/effector maturation of naïve (singleton TCR) T cells. After infection, the TCR repertoire became less diverse for both Tac/MTX and PT-Cy (log-2-fold singleton change -0.17 and -1.2 p = 0.0006 and 0.01) indicating that singletons in both cohorts were capable of expanding to pathogens. However the markedly decreased # singletons in PT-Cy at all timepoints was associated with significantly fewer singletons prior to infection (mean 3979 at 5K read-depth for Tac/MTX vs 2820 for PT-Cy p<0.001). This singleton deficit would place PT-Cy patients at higher risk of missing the critical mass of TCRs required to respond effectively to infections, consistent with their increased rate of Gr 2 infections. Conclusions: We performed longitudinal TCR-Seq on >200 million T cells from 324 HCT patients, representing the largest post-HCT TCR-Seq analysis in the history of the field, and enabling novel insights into TCR dynamics. These data identify a previously unappreciated global TCR diversity bottleneck with PT-Cy that simultaneously protects patients from cGVHD and places them at higher risk of infectious complications.

Abstract Chronic granulomatous disease (CGD) is a primary immunodeficiency characterized by life-threatening infections and inflammatory conditions. Hematopoietic cell transplantation (HCT) is the definitive treatment for CGD, but questions remain regarding patient selection and impact of active disease on transplant outcomes. We performed a multi-institutional retrospective and prospective study of 391 patients with CGD treated either conventionally (non-HCT) enrolled from 2004 to 2018 or with HCT from 1996 to 2018. Median follow-up after HCT was 3.7 years with a 3-year overall survival of 82% and event-free survival of 69%. In a multivariate analysis, a Lansky/Karnofsky score <90 and use of HLA-mismatched donors negatively affected survival. Age, genotype, and oxidase status did not affect outcomes. Before HCT, patients had higher infection density, higher frequency of noninfectious lung and liver diseases, and more steroid use than conventionally treated patients; however, these issues did not adversely affect HCT survival. Presence of pre-HCT inflammatory conditions was associated with chronic graft-versus-host disease. Graft failure or receipt of a second HCT occurred in 17.6% of the patients and was associated with melphalan-based conditioning and/or early mixed chimerism. At 3 to 5 years after HCT, patients had improved growth and nutrition, resolved infections and inflammatory disease, and lower rates of antimicrobial prophylaxis or corticosteroid use compared with both their baseline and those of conventionally treated patients. HCT leads to durable resolution of CGD symptoms and lowers the burden of the disease. Patients with active infection or inflammation are candidates for transplants; HCT should be considered before the development of comorbidities that could affect performance status. This trial was registered at www.clinicaltrials.gov as #NCT02082353.

Abstract Allogeneic hematopoietic cell transplantation (allo‐HCT) is a potentially curative treatment for acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). While many factors influence the outcomes of allo‐HCT, the independent impact of donor–recipient ABO mismatching remains unclear. Using the Center for International Blood and Marrow Transplant Research (CIBMTR) database, we identified patients aged ≥18 years with AML or ALL who underwent allo‐HCT between 2008 and 2018. Our objectives were to analyze the outcomes of allo‐HCT based on the donor–recipient ABO status (match, minor mismatch, major mismatch, bidirectional mismatch). Among 4946 eligible patients, 2741 patients (55.4%) were ABO matched, 1030 patients (20.8%) had a minor ABO mismatch, 899 patients (18.1%) had a major ABO mismatch, and 276 patients (5.6%) had a bidirectional ABO mismatch. In multivariable analyses, compared to ABO matched allo‐HCT, the presence of a major ABO mismatch was associated with worse overall survival (HR 1.16, 95% CI 1.05–1.29; p = 0.005), inferior platelet engraftment (HR 0.83, 95% CI 0.77–0.90; p < 0.001), and higher primary graft failure (HR 1.60, 95% CI 1.12–2.30, p = 0.01). Relapse, acute graft versus host disease (GVHD) grades III‐IV and chronic GVHD were not significantly associated with ABO status. While donor age was not significantly associated with outcomes, older recipient age was associated with worse survival and non‐relapse mortality. Our study demonstrates that donor–recipient ABO status is independently associated with survival and other post‐transplantation outcomes in acute leukemia. This underscores the importance of considering the ABO status in donor selection algorithms and its impact in acute leukemia.

7571 Background: In clinical trials of CAR T-cell therapies and real-world studies published to date, there is a paucity of data on outcomes by race and ethnicity. Here, we examined outcomes by race and ethnicity among LBCL pts who received axi-cel in the real-world setting. Methods: A total of 1389 pts with LBCL were identified from a non-interventional post-authorization safety study with pts receiving commercial axi-cel between 10/2017 and 08/2020. Race (African American or Asian vs White) and ethnicity (Hispanic vs non-Hispanic) were self-reported by pts. Pts with rescinded consent, enrolled in trials, having prior non-HCT cellular therapy, primary CNS lymphoma, unknown comorbidity or data in query were excluded. Median follow-up was 12.7 mo. Outcomes included ORR, CR rate, DOR, PFS and OS, grade ≥ 3 CRS (Lee 2014 criteria) and ICANS (ASTCT consensus grade). ORR and CR were evaluated in pts with ≥ 180 days of follow-up. Kaplan-Meier estimates were calculated for PFS and OS. Multivariable analyses comparing race and ethnicity were conducted via logistic and Cox regression. Results: Among all, 1127 (81%) were White, 70 (5%) African American and 81 (6%) Asian; 152 (11%) were Hispanic including 104 White, 2 Black, and 1 Asian Hispanic. African Americans, compared to White, were younger (median age 55.5 vs 62.8 years), more likely to have pulmonary impairment (41% vs 28%) and tended to have longer time from diagnosis (≥ 12 mo 71% vs 59%). Hispanic pts were younger (median age 58.5 vs 62.6 years) than non-Hispanic pts. ORR was 74% (CR 57%, 12-mo PFS and OS 48% and 63%) for White, 57% (CR 45%, 12-mo PFS and OS 36% and 62%) for African American, 67% (CR 53%, 12-mo PFS and OS 55% and 65%) for Asian and 73% (CR 55%, 12-mo PFS and OS 50% and 65%) for Hispanic pts. Grade ≥ 3 CRS and ICANS occurred in 7% and 18% of African American, 10% and 19% of Asian, and 8% and 27% of White pts, respectively. Hispanic pts had lower rates of grade ≥ 3 CRS and ICANS (4% and 15%) vs non-Hispanic (9% and 27%). African American race was associated with inferior ORR (OR 0.40; 95% CI, 0.24-0.69) and CR rate (OR 0.55; 95% CI 0.32-0.93) vs White. Asian pts had favorable DOR compared to both White (HR 0.46; 95% CI 0.24-0.87) and African American (HR 0.39; 95% CI 0.17-0.88). No statistical differences were found in OS and PFS across races, nor in any efficacy outcome between Hispanic and non-Hispanic pts. Asian (OR 0.52; 95% CI 0.29-0.96 vs White) and Hispanic pts (OR 0.51; 95% CI 0.31-0.85 vs non-Hispanic) had lower risk of grade ≥ 3 ICANS. Conclusions: Overall, axi-cel showed favorable OS, PFS and safety profile regardless of race and ethnicity in the real-world setting. No notable differences in outcomes were observed for Hispanic or Asian pts. Lower response rates in African American pts noted here warrant further investigation including any underrepresentation not explained by a lower incidence rate for DLBCL (SEER), access to care, and disease burden.

PURPOSE Calcineurin inhibitors (CNI) are standard components of graft-versus-host disease (GVHD) prophylaxis after hematopoietic cell transplantation (HCT). Prior data suggested that CNI-free approaches using donor T-cell depletion, either by ex vivo CD34 selection or in vivo post-transplant cyclophosphamide (PTCy) as a single agent, are associated with lower rates of chronic GVHD (cGVHD). METHODS This multicenter phase III trial randomly assigned patients with acute leukemia or myelodysplasia and an HLA-matched donor to receive CD34-selected peripheral blood stem cell, PTCy after a bone marrow (BM) graft, or tacrolimus and methotrexate after BM graft (control). The primary end point was cGVHD (moderate or severe) or relapse-free survival (CRFS). RESULTS Among 346 patients enrolled, 327 received HCT, 300 per protocol. Intent-to-treat rates of 2-year CRFS were 50.6% for CD34 selection (hazard ratio [HR] compared with control, 0.80; 95% CI, 0.56 to 1.15; P = .24), 48.1% for PTCy (HR, 0.86; 0.61 to 1.23; P = .41), and 41.0% for control. Corresponding rates of overall survival were 60.1% (HR, 1.74; 1.09 to 2.80; P = .02), 76.2% (HR, 1.02; 0.60 to 1.72; P = .95), and 76.1%. CD34 selection was associated with lower moderate to severe cGVHD (HR, 0.25; 0.12 to 0.52; P = .02) but higher transplant-related mortality (HR, 2.76; 1.26 to 6.06; P = .01). PTCy was associated with comparable cGVHD and survival outcomes to control, and a trend toward lower disease relapse (HR, 0.52; 0.28 to 0.96; P = .037). CONCLUSION CNI-free interventions as performed herein did not result in superior CRFS compared with tacrolimus and methotrexate with BM. Lower rates of moderate and severe cGVHD did not translate into improved survival.

Abstract Introduction: The gut microbiome is a potentially modifiable factor in treatment related outcomes in allogeneic hematopoietic cell transplant (HCT). Prior studies have linked pre- or mid-treatment gut microbiome diversity with risk for treatment related morbidity and mortality. However, these studies have been limited by the inclusion of one or only a few institutions and the lack of longitudinal sampling with high quality metadata. These limitations complicate the interpretation of microbiome alterations over the course of HCT. Methods: To overcome these, we devised and implemented a large-scale biospecimen collection protocol in conjunction with BMT CTN 1703, a randomized, multicenter, Phase III trial of tacrolimus/methotrexate vs. post-transplant cyclophosphamide/tacrolimus/mycophenolate mofetil in reduced intensity conditioning (RIC) allogeneic HCT (NCT03959241). Patients enrolled on 1703 were optionally co-enrolled in the companion immune and microbiome profiling study, 1801 (MI-IMMUNE). This involved blood, urine and stool sampling before conditioning (PCON), then weekly starting on day 0 through day 77 (through day 84 for blood), and on days 98, 180, 270, 365 and 730. For all enrolled participants where the donor consented, residual donor cells were saved from the empty hematopoietic stem cell product bag for later analysis. Additionally, the protocol included one-time blood, urine and stool sample collection from consented matched related donors (MRDs) prior to stem cell collection. Starting with protocol version 4.0 on February 1, 2021, participation in 1801 stool collection was required for the first six out of eighteen sample collection timepoints. Participation in later stool and urine timepoint collections remained optional. Here we review the feasibility of creating a multi-institutional biobank. Additionally, we assess the success of our strategies by calculating sample collection compliance and standard deviation in compliance across centers for each timepoint. Results: On June 18, 2021, BMT CTN 1703/1801 closed to accrual with 431 patients enrolled on 1703; 323 patients from 36 centers were co-enrolled on 1801. 304 (94%) provided study samples, making this the largest prospective microbiome and immune profiling study in HCT patients to date. As of July 6, 2021, 3,683 blood, 2,668 urine, and 2,098 stool samples had been collected. Across the first 6 timepoints for all participating centers, blood, urine and stool sample collection averaged 93%, 82%, and 74% compliance, respectively. Of the 99 (30%) patients enrolled on 1801 with a MRD, 34 (34%) donors consented to sample collection. Sample collection compliance was lower for MRDs than for patients on the study with 76%, 74%, and 62% of expected blood, urine and stool samples collected, respectively, from this group. For stool collection exclusively, a median of 5 samples were collected per patient across the first 6 timepoints (median of 6 across all timepoints) with 93 (31%) of patients completing a full sample set through Day 28. 139 (46%) patients provided at least one sample after day 28; these represented 37% of the total samples collected to date. The PCON sample, which provides an important measure of pre-treatment gut microbiome diversity, had the third highest compliance with 74% of patients providing a sample. Surprisingly, Day 28 had the lowest compliance (66%) and highest standard deviation (37%) possibly because this timepoint often falls around the time of hospital discharge. Between PCON and day 28, the standard deviation between sites in the average collection compliance (24%) and number of samples collected per patient (1.1) was small indicating the successful adoption of stool collection across institutions. Table 1 summarizes sample collection statistics. Conclusion: Overall this study has resulted in a large, novel biobank of blood, urine and stool samples from patients undergoing RIC allogeneic HCT at 36 centers across the US. This will serve as a valuable resource for investigating the role of the gut microbiome in long term health outcomes following HCT. Although the results of 1801 are forthcoming given ongoing sample collection, the size and composition of the biobank to date clearly demonstrate the feasibility of implementing multi-institutional stool collection. This study represents a critical step towards the large-scale adoption of microbiome sampling as a diagnostic tool. Figure 1 Figure 1. Disclosures Chhabra: GSK: Honoraria. Clark: Kadmon: Consultancy. Horowitz: Mesoblast: Research Funding; Shire: Research Funding; Vertex: Research Funding; Stemcyte: Research Funding; Vor Biopharma: Research Funding; Janssen: Research Funding; Miltenyi Biotech: Research Funding; Kiadis: Research Funding; Sobi: Research Funding; Kite/Gilead: Research Funding; Pfizer, Inc: Research Funding; Jazz Pharmaceuticals: Research Funding; Magenta: Consultancy, Research Funding; Medac: Research Funding; Novartis: Research Funding; GlaxoSmithKline: Research Funding; Daiicho Sankyo: Research Funding; Xenikos: Research Funding; Omeros: Research Funding; Orca Biosystems: Research Funding; Pharmacyclics: Research Funding; Regeneron: Research Funding; Tscan: Research Funding; Takeda: Research Funding; CSL Behring: Research Funding; Genentech: Research Funding; Gamida Cell: Research Funding; Chimerix: Research Funding; Bristol-Myers Squibb: Research Funding; bluebird bio: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Allovir: Consultancy; Actinium: Research Funding; Sanofi: Research Funding; Seattle Genetics: Research Funding. Jenq: Microbiome DX: Consultancy; Merck: Consultancy; Prolacta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kaleido: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seres: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; LisCure: Consultancy, Membership on an entity's Board of Directors or advisory committees; MaaT Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karius: Consultancy. Levine: Equillium Bio: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Research Funding; Kamada: Research Funding; Biogen: Research Funding; Omeros: Membership on an entity's Board of Directors or advisory committees; Symbio: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Talaris Therapeutics: Membership on an entity's Board of Directors or advisory committees; Viracor: Patents & Royalties: GVHD biomarker patent with royalties from Viracor; Mesoblast: Consultancy, Research Funding; X4 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Murthy: CRISPR Therapeutics: Research Funding. Riches: ATARA Biotherapeutics: Other: Payment; BioIntelect: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Other: Payment. Sung: Merck: Research Funding; Novartis: Research Funding; Enterome: Research Funding; Seres: Research Funding; AVROBIO: Consultancy; Abbott Nutrition: Honoraria; Clasado: Other: Research Product; DSM: Other: Research Product. Al Malki: Neximmune: Consultancy; Jazz Pharmaceuticals, Inc.: Consultancy; Rigel Pharma: Consultancy; Hansa Biopharma: Consultancy; CareDx: Consultancy. Rezvani: Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding; US Department of Justice: Consultancy. Bolaños-Meade: Incyte Corp: Consultancy. Holtan: Incyte: Consultancy, Research Funding; Generon: Consultancy. Saber: Govt. COI: Other. Hamadani: Sanofi, Genzyme, AstraZeneca, BeiGene: Speakers Bureau; Janssen, Incyte, ADC Therapeutics, Omeros, Morphosys, Kite: Consultancy; Takeda, Spectrum Pharmaceuticals and Astellas Pharma: Research Funding. Kean: Bluebird Bio: Research Funding; Bristol Myers Squibb: Patents & Royalties: From clinical trial data, Research Funding; Vertex: Consultancy; Novartis: Consultancy; Gilead: Research Funding; Regeneron: Research Funding; EMD Serono: Consultancy. Perales: Cidara: Honoraria; Servier: Honoraria; Incyte: Honoraria, Other; Equilium: Honoraria; Takeda: Honoraria; Novartis: Honoraria, Other; Nektar Therapeutics: Honoraria, Other; NexImmune: Honoraria; MorphoSys: Honoraria; Omeros: Honoraria; Karyopharm: Honoraria; Sellas Life Sciences: Honoraria; Merck: Honoraria; Miltenyi Biotec: Honoraria, Other; Medigene: Honoraria; Bristol-Myers Squibb: Honoraria; Kite/Gilead: Honoraria, Other; Celgene: Honoraria.

Abstract BACKGROUND: Our group recently reported on the results of Blood and Marrow Transplant (BMT) Clinical Trials Network (CTN) 1101 a randomized comparison between double umbilical cord blood (dUCB) and haploidentical bone marrow (haplo) with post-transplant cyclophosphamide (ptCy) in the nonmyeloablative setting that showed similar progression free survival (PFS) between the two treatment groups, but lower non-relapse mortality (NRM) and better of overall survival (OS) in the haplo arm. In this secondary analysis we sought to investigate if transplant center experience with haplo and or cord blood HCT had an impact on outcomes. PATIENTS AND METHODS: All patient randomized in BMT CTN 1101 were included. In order to determine the transplant center experience with either haplo or dUCB we queried the Center for International Blood and Marrow Transplant Research (CIBMTR) for number of transplants with each platform in the year prior to initiation of the study. Centers were then grouped as dUCB center (&gt; 10 dUCB, n=117, 10 centers), Haplo center (&gt;10 haplo and ≤10 dUCB, n=110, 2 centers), and ≤10 haplo and ≤10 dUCB HCTs (other center, n=140, 21 centers). Further analysis considered the alternative cut-off for haplo (&gt; 5 vs ≤ 5) experience, and considered the outcomes based on the donor experience vs. others (e.g. dUCB &gt; 10 vs. ≤ 10; haplo &gt; 5 vs. ≤ 5). RESULTS: The effect of center experience on HCT outcomes shown in Figure, below . After adjusting for age, Karnofsky performance score and, disease risk index we found that there was no difference in outcomes between haplo and dUCB for centers that were experienced with dUCB or had limited to no experience with either dUCB or haplo. In contrast, in centers that were primarily experienced with haplo had better outcomes with this donor type, as compared to dUCB. The higher risk of treatment failure (relapse or death) and overall mortality in dUCB in haplo experienced centers was driven by significantly higher risk of relapse. We then considered the transplant experience with each of the donor types separately. In transplant centers that had performed &gt; 10 dUCB, there were similar outcomes for recipients of both dUCB and haplo. Similarly, centers that had ≤ 5 haplo HCTs had no difference in outcomes between donor types suggesting an overlap with centers that had performed &gt; 10 dUCB HCTs. Overall mortality was higher among dUCB recipients in centers that had performed ≤ 10 dUCB. Notably, the hazard ratio of non-relapse mortality favored haplo in all four donor experience type of transplant center, albeit not statistically significant. CONCLUSION: Except for dUCB recipients in centers with &lt; 10 dUCB/year had worse overall mortality, primarily driven by relapse, the transplant center experience in the year prior to the initiation of BMT CTN 1101 had limited impact on the outcomes of this randomized clinical trial. Figure 1 Figure 1. Disclosures Brunstein: NANT: Research Funding; FATE: Research Funding; GamidaCell: Research Funding; BlueRock: Research Funding; AlloVir: Consultancy. Costa: Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria. Cutler: Deciphera: Consultancy; Cimeio: Consultancy; Editas: Consultancy; Kadmon: Consultancy; Pfizer: Consultancy; Mallinckrodt: Consultancy; CareDx: Consultancy; Incyte: Consultancy; Omeros: Consultancy; Syndax: Consultancy; Mesoblast: Consultancy; Jazz: Consultancy. Horowitz: Sobi: Research Funding; Regeneron: Research Funding; Orca Biosystems: Research Funding; Tscan: Research Funding; Xenikos: Research Funding; Miltenyi Biotech: Research Funding; Stemcyte: Research Funding; Medac: Research Funding; Vor Biopharma: Research Funding; Kite/Gilead: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Kiadis: Research Funding; Seattle Genetics: Research Funding; Mesoblast: Research Funding; GlaxoSmithKline: Research Funding; Sanofi: Research Funding; Pfizer, Inc: Research Funding; Omeros: Research Funding; Magenta: Consultancy, Research Funding; Jazz Pharmaceuticals: Research Funding; Vertex: Research Funding; Genentech: Research Funding; Takeda: Research Funding; Novartis: Research Funding; Shire: Research Funding; Gamida Cell: Research Funding; Daiicho Sankyo: Research Funding; CSL Behring: Research Funding; Chimerix: Research Funding; Bristol-Myers Squibb: Research Funding; bluebird bio: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Allovir: Consultancy; Actinium: Research Funding. Horwitz: Gamida Cell: Research Funding. McGuirk: Novartis: Research Funding; Magenta Therapeutics: Consultancy, Honoraria, Research Funding; EcoR1 Capital: Consultancy; Pluristem Therapeutics: Research Funding; Novartis: Research Funding; Bellicum Pharmaceuticals: Research Funding; Astelllas Pharma: Research Funding; Gamida Cell: Research Funding; Fresenius Biotech: Research Funding; Allovir: Consultancy, Honoraria, Research Funding; Juno Therapeutics: Consultancy, Honoraria, Research Funding; Kite/ Gilead: Consultancy, Honoraria, Other: travel accommodations, expense, Kite a Gilead company, Research Funding, Speakers Bureau. Rezvani: US Department of Justice: Consultancy; Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding. Rybka: Spark Therapeutics: Consultancy; Merck: Consultancy. Vasu: Kiadis, Inc.: Research Funding; Boehringer Ingelheim: Other: Travel support; Seattle Genetics: Other: travel support; Omeros, Inc.: Membership on an entity's Board of Directors or advisory committees.

Abstract Background: Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative treatment for acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). While many factors influence the outcomes of allo-HCT in these leukemias, the independent impact of ABO mismatching between the patient and donor remains unclear. Methods: Using the CIBMTR database, we identified adults aged ≥18 years with AML or ALL who underwent allo-HCT from HLA-matched sibling donor (MSD) or 8/8 matched unrelated donor (MUD) between 2008-2018. We excluded patients who underwent transplant from a mismatched donor source or who received an ex-vivo T-cell depleted graft. Patients were stratified into cohorts based on ABO status (match, minor mismatch, major mismatch, bidirectional mismatch). Outcomes such as overall survival (OS), disease free survival (DFS), non-relapse mortality (NRM), relapse, incidence of acute graft versus host disease (GVHD), chronic GVHD, neutrophil engraftment, platelet engraftment and graft failure were evaluated. Survival analysis was done using Kaplan-Meier method and significant predictors were evaluated using Cox-proportional hazard regression method. Multivariate regression model included main effect (ABO status) and covariates (patient age, gender match, disease type, disease status, HCT-CI, Karnofsky performance status, donor type, conditioning intensity/use of TBI, stem cell source, GVHD prophylaxis, ATG/alemtuzumab use, transplant year). Results: Of 4946 patients who met the study criteria, 2741 patients (55.4%) were ABO matched, 1030 patients (20.8%) had minor ABO mismatch, 899 patients (18.1%) had major ABO mismatch and 276 patients (5.6%) had bidirectional ABO mismatch. Graft manipulation for ABO incompatibility was performed in 900 patients (minor ABO mismatch=532; major ABO mismatch=226; bidirectional mismatch=142), however, the information on individual graft manipulation techniques was limited. In multivariable analysis (table 1), major ABO mismatch significantly affected the OS, platelet engraftment and primary graft failure. Compared to ABO matched allo-HCT, major ABO mismatched allo-HCT was associated with worse OS (major mismatch - HR 1.16, 95% CI 1.05-1.29; p=0.005), inferior platelet engraftment (HR 0.83, 95% CI 0.77-0.90; p=&lt;0.001), and higher risk of primary graft failure [4.5% (major mismatch) vs. 3.2% (ABO matched) - HR 1.60, 95% CI 1.12-2.30, p=0.01]. There was a significant interaction between the ABO status and graft type (peripheral blood vs. bone marrow) for the acute GVHD grades 2-4 model, and they are presented separately (table 1). Bidirectional ABO mismatch also significantly impacted the outcomes such as acute GVHD grades 2-4 (in bone marrow stem cell subgroup, HR 0.50, 95%CI 0.27-0.93, p=0.02) in addition to a trend towards inferior survival and NRM (p-value not significant). Other outcomes such as relapse (p=0.41), acute GVHD grades 3-4 (p=0.13), and chronic GVHD (p=0.30) were not significantly influenced by the ABO status. Conclusions: Our study demonstrates that pre-transplant ABO status is an independent predictor of survival and other post-transplant outcomes in a large cohort of patients with AML and ALL undergoing allo-HCT in the recent era. This demonstrates the importance of considering ABO status in the donor selection algorithms and potential strategies to mitigate its adverse impact. Due to the limited information available on graft manipulation strategies, the impact of graft manipulation techniques on the outcomes could not be evaluated and needs to be investigated in future studies. Figure 1 Figure 1. Disclosures Guru Murthy: Techspert: Consultancy; Guidepoint: Consultancy; Cancerexpertnow: Honoraria; Qessential: Consultancy; TG therapeutics: Other: Advisory board; Cardinal Health Inc.: Honoraria. Devine: Magenta Therapeutics: Current Employment, Research Funding; Tmunity: Current Employment, Research Funding; Sanofi: Consultancy, Research Funding; Johnsonand Johnson: Consultancy, Research Funding; Orca Bio: Consultancy, Research Funding; Be the Match: Current Employment; Vor Bio: Research Funding; Kiadis: Consultancy, Research Funding. Farhadfar: Incyte: Consultancy. Sharma: Vertex Pharmaceuticals/CRISPR Therapeutics: Other: Salary support paid to institution; Novartis: Other: Salary support paid to institution; Spotlight Therapeutics: Consultancy; Medexus Inc: Consultancy; CRISPR Therapeutics: Other, Research Funding; Vindico Medical Education: Honoraria. Stefanski: Novartis: Honoraria. Pulsipher: Equillium: Membership on an entity's Board of Directors or advisory committees; Adaptive: Research Funding; Jasper Therapeutics: Honoraria. Shaw: mallinkrodt: Other: payments; Orca bio: Consultancy.

PURPOSE Allogeneic hematopoietic cell transplantation (HCT) is the only potentially curative therapy for myelodysplastic syndromes (MDS), although it is infrequently offered to older patients. The relative benefits of HCT over non-HCT therapy in older patients with higher-risk MDS have not been defined. METHODS We conducted a multicenter biologic assignment trial comparing reduced-intensity HCT to hypomethylating therapy or best supportive care in subjects 50-75 years of age with intermediate-2 or high-risk de novo MDS. The primary outcome was overall survival probability at 3 years. Between January 2014 and November 2018, we enrolled 384 subjects at 34 centers. Subjects were assigned to the Donor or No-Donor arms according to the availability of a matched donor within 90 days of study registration. RESULTS The median follow-up time for surviving subjects was 34.2 months (range: 2.3-38 months) in the Donor arm and 26.9 months (range: 2.4-37.2 months) in the No-Donor arm. In an intention-to-treat analysis, the adjusted overall survival rate at 3 years in the Donor arm was 47.9% (95% CI, 41.3 to 54.1) compared with 26.6% (95% CI, 18.4 to 35.6) in the No-Donor arm ( P = .0001) with an absolute difference of 21.3% (95% CI, 10.2 to 31.8). Leukemia-free survival at 3 years was greater in the Donor arm (35.8%; 95% CI, 29.8 to 41.8) compared with the No-Donor arm (20.6%; 95% CI, 13.3 to 29.1; P = .003). The survival benefit was seen across all subgroups examined. CONCLUSION We observed a significant survival advantage in older subjects with higher-risk MDS who have a matched donor identified and underwent reduced-intensity HCT, when compared with those without a donor. HCT should be included as an integral part of MDS management plans in fit older adults with higher-risk MDS.